How a Ball Valve Manufacturer Uses Open Source StyleBI

In the competitive and precision-driven world of industrial manufacturing, data-driven decision-making can define success or failure. For a mid-sized manufacturer of ball valves serving global energy, waterworks, and OEM clients, the challenge was not collecting data—it was transforming fragmented data into actionable insights. The company had a wealth of production, sales, inventory, and supply chain data housed in legacy ERP systems, spreadsheets, and sensor logs. What they lacked was a unified, scalable platform to analyze it efficiently across departments. That's when the firm adopted InetSoft’s open source StyleBI, a SaaS business intelligence (BI) software solution that helped them bridge gaps between operations and strategy with a modern, self-service analytics platform.

Challenges Before StyleBI

Prior to deploying StyleBI, the company relied heavily on manual reporting. Production data was pulled weekly from MES logs into Excel, inventory snapshots were compiled ad hoc, and sales forecasting was driven more by gut feeling than data-backed KPIs. With growing demand from both domestic and international markets, executives recognized the urgent need for real-time visibility into operations and customer trends. IT leaders sought a BI tool that could integrate with their existing systems, offer visual analytics, and empower users with little technical experience to explore data on their own. Budget constraints made a large-scale proprietary BI solution infeasible, leading them to explore open-source options with SaaS scalability.

Why StyleBI Was Chosen

StyleBI stood out for three key reasons: its open-source framework, its cloud-native deployment capabilities, and its ease of integration. The IT team was impressed with its support for schema-less data mashups, which allowed them to blend structured ERP data with semi-structured sensor logs and Excel files without building a rigid data warehouse. This agility was critical for a manufacturer where engineering and production processes evolve rapidly. Furthermore, StyleBI’s modular architecture meant the team could start small and grow functionality over time—ideal for resource-constrained teams needing quick wins.

Key Performance Indicators Tracked

The ball valve manufacturer identified several core KPIs to track across business units:

• First Pass Yield (FPY): Measures the percentage of products manufactured correctly the first time without rework.
• Overall Equipment Effectiveness (OEE): Captures how efficiently production equipment is utilized, including availability, performance, and quality metrics.
• Order Cycle Time: Measures the time from order receipt to shipment, highlighting fulfillment efficiency.
• Inventory Turnover Ratio: Tracks how often inventory is sold and replaced, helping control carrying costs.
• On-Time Delivery Rate (OTD): Monitors how reliably the company meets customer delivery expectations.
• Sales by Product Line and Region: Provides visibility into revenue distribution and growth trends.
• Supplier Lead Time Variability: Identifies delays in inbound materials affecting production schedules.

Dashboards and Visualizations

Using StyleBI’s drag-and-drop interface, the IT team quickly built customized dashboards tailored to production, supply chain, and executive stakeholders. Production managers use a real-time dashboard showing:

• A line chart tracking daily FPY percentages across multiple production lines
• A gauge chart indicating current OEE against target benchmarks
• A stacked bar chart for machine downtime by cause (e.g., maintenance, operator error)
• A heatmap correlating shift patterns with defect rates

Meanwhile, the supply chain team built a dashboard featuring:

• A column chart showing supplier lead times by part category
• A geographic map of supplier distribution with color-coded reliability scores
• A scatter plot comparing inbound material delays with order fulfillment lags

For executives, StyleBI delivered a high-level scorecard combining KPIs across the business, including:

• A bullet graph for revenue vs. goal, segmented by region
• A trendline chart showing 12-month margin progression
• Interactive filter widgets for product line, quarter, and customer segment

Embedded Analytics and Self-Service Reporting

One standout capability of StyleBI was its embedded analytics functionality. The IT team embedded dashboards directly into the company’s internal portal used by engineers, managers, and customer service reps. Each user role was assigned data access permissions through StyleBI’s security model, ensuring that sensitive financial or operational data was restricted appropriately. Business users could also build their own visual reports using pre-approved datasets—eliminating dependency on IT for day-to-day insights.

For example, a quality control manager created a personal dashboard comparing defect trends across three valve models, with filters for operator and shift. A sales analyst built a quarterly forecast model using StyleBI’s calculated fields to apply seasonal multipliers to historical sales data. The ability for non-developers to experiment and iterate quickly led to faster insights and improved decision-making across the company.

Benefits Realized

After just three months of using StyleBI, the company saw substantial benefits:

• Production efficiency increased by 9% due to improved visibility into machine uptime and defect drivers.
• Inventory costs were reduced by 11% as inventory turnover ratios improved with more accurate demand forecasting.
• On-time delivery rates improved by 6% thanks to better coordination between purchasing and production.
• Data reporting time dropped by 70%, with users now building their own dashboards instead of waiting for IT.
• Cross-functional collaboration increased as teams could share live dashboards in project planning sessions.

Technical Considerations

StyleBI’s API and connector framework made it easy to ingest data from the manufacturer’s PostgreSQL ERP database, Excel files from procurement, and IoT data from production machines via CSV exports. The IT team used scheduled data refreshes and delta loading to optimize performance without overburdening the network. Because the software is open-source, the team also customized UI components and added lightweight branding to align with the company’s internal systems.

Cloud deployment was handled using Kubernetes on a managed service provider. StyleBI’s microservices-friendly architecture ensured resilience and fast scaling during monthly reporting cycles. System admins configured alerts to monitor query performance, disk usage, and user access anomalies, ensuring system stability and compliance with internal data governance policies.

Future Plans

Buoyed by the success of the initial rollout, the company is now planning to expand its use of StyleBI into predictive analytics. The IT team is exploring integration with Python-based forecasting models to predict machine failures and optimize preventive maintenance schedules. There’s also interest in using StyleBI’s webhooks to trigger real-time alerts for threshold breaches in KPIs—such as production bottlenecks or sales dips—enabling faster interventions.

The company also intends to create customer-facing dashboards for large OEM clients, offering visibility into their own order statuses and delivery schedules. This will be made possible through StyleBI’s embedded analytics and customizable access permissions. By layering insights across internal operations and external customer service, the manufacturer hopes to deepen customer relationships and differentiate itself in a highly commoditized market.